6 papers
LuxIA: A Lightweight Unitary matriX-based Framework Built on an Iterative Algorithm for Photonic Neural Network Training
Tzamn Melendez Carmona, Federico Marchesin, Marco P. Abrate +3
PNNs present promising opportunities for accelerating machine learning by leveraging the unique benefits of photonic circuits. However, current state of the art PNN simulation tool…
Power Side-Channel Analysis of the CVA6 RISC-V Core at the RTL Level Using VeriSide
Behnam Farnaghinejad, Antonio Porsia, Annachiara Ruospo +3
Security in modern RISC-V processors demands more than functional correctness: It requires resilience to side-channel attacks. This paper evaluates the vulnerability of the side ch…
Uncovering Privacy Vulnerabilities through Analytical Gradient Inversion Attacks
Tamer Ahmed Eltaras, Qutaibah Malluhi, Alessandro Savino +2
Federated learning has emerged as a prominent privacy-preserving technique for leveraging large-scale distributed datasets by sharing gradients instead of raw data. However, recent…
CANDoSA: A Hardware Performance Counter-Based Intrusion Detection System for DoS Attacks on Automotive CAN bus
Franco Oberti, Stefano Di Carlo, Alessandro Savino
The Controller Area Network (CAN) protocol, essential for automotive embedded systems, lacks inherent security features, making it vulnerable to cyber threats, especially with the…
Energy-Efficient Digital Design: A Comparative Study of Event-Driven and Clock-Driven Spiking Neurons
Filippo Marostica, Alessio Carpegna, Alessandro Savino +1
This paper presents a comprehensive evaluation of Spiking Neural Network (SNN) neuron models for hardware acceleration by comparing event driven and clock-driven implementations. W…
Braided interferometer mesh for robust photonic matrix-vector multiplications with non-ideal components
Federico Marchesin, Matěj Hejda, Tzamn Melendez Carmona +5
Matrix-vector multiplications (MVMs) are essential for a wide range of applications, particularly in modern machine learning and quantum computing. In photonics, there is growing i…